In PCBA manufacturing the BOM drives procurement, production and quality control, and every entry needs 20+ structured parameters copied by hand from component datasheets. ETAO Tech built a BOM auto-fill assistant on MOI that parses complex layouts and extracts them.
Founded in 2012, ETAO Tech is a software and IT services provider to the electronics manufacturing industry, serving over a hundred digital factories. Its PCBA (Printed Circuit Board Assembly) software covers BOM preparation, procurement and quality control, and its clients-contract manufacturers, EMS providers and electronics OEMs-manage thousands of components across their product lines, each defined by a detailed manufacturer datasheet.
In PCBA manufacturing, the Bill of Materials (BOM) is the master document driving procurement, production, and quality control. Each BOM entry requires 20+ structured fields-part number, manufacturer, package type (SMD/PTH), package form, dimensions, lead count, MSL rating, mounting method, and more. This information is buried inside manufacturer datasheets-dense, multi-page PDF documents with mixed layouts of text, tables, technical drawings, and dimensional diagrams. Engineers manually read each datasheet, locate the relevant parameters, and transcribe them into BOM spreadsheets-a process that is slow, error-prone, and does not scale.
ETAO Tech deployed an AI BOM Auto-Fill Assistant on OmniFabric that automatically ingests component datasheets, parses complex document layouts, extracts key parameters using LLM-powered document intelligence, validates against predefined field schemas and enumeration rules, and populates structured BOM entries ready for production use.
Engineers no longer manually read datasheets and transcribe parameters-the AI pipeline extracts package type, dimensions, MSL, lead configuration, and 20+ other fields directly from source documents.
The document intelligence engine handles the full variety of datasheet formats-multi-column tables, dimensional drawings, mixed text-and-diagram pages-that defeat traditional rule-based parsers.
Every extracted value is validated against predefined enumerations and field constraints before entering the BOM, catching errors that manual transcription routinely introduces.